Predicting master transcription factors from pan-cancer expression data
J. Reddy, M. A. S. Fonseca, R. I. Corona, R. Nameki, F. Segato Dezem, I. A. Klein, H. Chang, D. Chaves-Moreira, L. Afeyan, T. M. Malta, X. Lin, F. Abbasi, A. Font-Tello, T. Sabedot, P. Cejas, , K. Lawrenson
This paper introduces CaCTS, an algorithm that identifies candidate master transcription factors (MTFs) across 34 cancer types using RNA-seq data, revealing novel MTFs and functional groupings.
bioRxiv · Nov 12, 2019Cancer Biology